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Using Kinect™ sensor in observational methods for assessing postures at work.

Jose Antonio Diego-Mas1, Jorge Alcaide-Marzal1

  • 1Engineering Projects Department, I3BH (Labhuman), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain.

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This study shows that Kinect™ range sensors can accurately assess postural loads for ergonomic risk assessment when the worker faces the sensor. Sensor view angle significantly impacts posture classification accuracy, requiring further research for real-world applications.

Keywords:
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Area of Science:

  • Ergonomics and Human Factors
  • Biomechanical Engineering
  • Wearable Technology

Background:

  • Traditional observational methods for assessing postural loads can be time-consuming and subjective.
  • Attaching sensors or markers to subjects can be intrusive and impractical in some environments.
  • Low-cost range sensors offer a potential non-intrusive alternative for capturing joint kinematics.

Purpose of the Study:

  • To evaluate the efficacy of the Kinect™ range sensor for observational ergonomic assessments.
  • To compare Kinect™-based posture analysis with traditional human observer methods.
  • To determine the influence of sensor-to-worker angle on assessment accuracy.

Main Methods:

  • Implementation of a computerized OWAS (Ovako Working Posture Analyzing System) ergonomic assessment system.
  • Data acquisition using the Kinect™ range sensor for joint position detection.
  • Comparison of automated risk level classification with human observer assessments.

Main Results:

  • High inter-method agreement (Proportion agreement index = 0.89, κ = 0.83) was observed when the subject was facing the sensor.
  • The sensor's point of view relative to the worker significantly influenced posture classification accuracy.
  • The Kinect™ system demonstrated promising results for identifying ergonomic risk levels.

Conclusions:

  • Kinect™ range sensors show potential for non-intrusive ergonomic postural load assessment.
  • Optimal sensor placement, particularly facing the worker, is crucial for accurate results.
  • Further investigation is needed to address limitations for real-world industrial applications.